Is a "real" C-Python possible?

[Jack]

I understand that the standard Python distribution is considered
the C-Python. Howerver, the current C-Python is really a combination
of C and Python implementation. There are about 2000 Python files
included in the Windows version of Python distribution. I'm not sure
how much of the C-Python is implemented in C but I think the more
modules implemented in C, the better performance and lower memory
footprint it will get.

I wonder if it's possible to have a Python that's completely (or at
least for the most part) implemented in C, just like PHP - I think
this is where PHP gets its performance advantage. Or maybe I'm wrong
because the core modules that matter are already in C and those Python
files are really a think wrapper. Anyhow, if would be ideal if Python
has performance similar to Java, with both being interpreted languages.

Jack

[Paul McGuire]

On Dec 9, 6:07 pm, "Jack" <nos...@invalid .comwrote:

Plus, Psyco is not the
main stream and has stopped development.

<scooby-whruu??>

What makes you think it has stopped development? I just swung by the
SF project page, and its most recent news post was just 2 months ago.

Psyco may not be in the standard Python distribution, but it is
definitely a fixture of the Python landscape, which is about as close
to main stream as you can get.

-- Paul

[Chris M]

On Dec 9, 10:04 pm, Paul McGuire <pt...@austin.r r.comwrote:

On Dec 9, 6:07 pm, "Jack" <nos...@invalid .comwrote:

Plus, Psyco is not the
main stream and has stopped development.

<scooby-whruu??>

What makes you think it has stopped development? I just swung by the
SF project page, and its most recent news post was just 2 months ago.

Psyco may not be in the standard Python distribution, but it is
definitely a fixture of the Python landscape, which is about as close
to main stream as you can get.

-- Paul

Maybe because of this line:

"Psyco is a reasonably complete project. I will not continue to
develop it beyond making sure it works with future versions of Python.
My plans for 2006 are to port the techniques implemented in Psyco to
PyPy. PyPy will allow us to build a more flexible JIT specializer,
easier to experiment with, and without the overhead of having to keep
in sync with the evolutions of the Python language."

[Bruno Desthuilliers]

Jack a écrit :

I understand that the standard Python distribution is considered
the C-Python. Howerver, the current C-Python is really a combination
of C and Python implementation. There are about 2000 Python files
included in the Windows version of Python distribution. I'm not sure
how much of the C-Python is implemented in C but I think the more
modules implemented in C, the better performance and lower memory
footprint it will get.

I wonder if it's possible to have a Python that's completely (or at
least for the most part) implemented in C, just like PHP - I think
this is where PHP gets its performance advantage.

Which "performanc e advantage" ???

Or maybe I'm wrong
because the core modules that matter are already in C and those Python
files are really a think wrapper. Anyhow, if would be ideal if Python
has performance similar to Java, with both being interpreted languages.

<mode="pedantic ">
Neither Python nor Java are "interprete d languages", because there's no
such thing as an "interprete d language" - being 'interpreted' (whatever
the definition of 'interpreted') is a quality of an implementation, not
of a language. wrt/ to CPython and Sun's Java implementation, they are
both byte-code compiled - which, according to usual definitions, is not
quite the same thing !-)
</mode>

Now most of the performance difference is due to Java being much less
dynamic than Python, which allow both the compiler and the VM to do much
more optimizations - specially JIT compilation. It's quite harder to
implement such optimizations for a language as dynamic as Python (IIRC,
some language/compiler gurus here mentionned that even compiling Python
to native binary code would not buy that much gain).

Actually, it seems that taking the opposite approach - that is, trying
to implement as much as possible of Python in Python - would be more
promising wrt/ possible JIT compilation, cf the Pypy project.

[Paul Boddie]

On Dec 9, 10:43 pm, "Jack" <nos...@invalid .comwrote:

>
http://blog.snaplogic.org/?p=55

There's some choice nonsense here, albeit on a different topic:

"Coding for wxwidgets, using a QT or GTK bridge, or using TCL/TK is
hardly an optimal solution when writing complex graphical
applications, and Java wins in this area, despite there comically
being many problems with the look and feel of Java applications."

Clearly an individual who hasn't actually used any of the Python GUI
development solutions, given the choice of words: "bridge", "hardly an
optimal solution"; virtually intimating that you'd be doing malloc/
free or new/delete all the time. Plus throwaway remarks of the form
"XYZ wins" tend to suggest beliefs with little substance and a
continual need for self-reassurance on such matters.

Anyway, back to the topic at hand...

Here's an article that shows the new version of Ruby is
faster than Python in some aspects (they are catching up :)

http://antoniocangiano.com/2007/11/2...19-smokes-pyth...

It's evident that the next mainstream version of Ruby will have
various optimisations around recursive operations - something that has
generally been rejected for CPython. Of course, the mainstream Ruby
implementation has had a lot of scope for improvement:

http://shootout.alioth.debian.org/gp...t=all&lang=all

What disappoints me somewhat is that most of the people interested in
taking Python performance to the next level are all outside (or on the
outer fringes of) the CPython core development group: PyPy and Shed
Skin are mostly distinct technologies; Psyco integrates with CPython
but hasn't improved the "out of the box" situation; Pyrex is really a
distinct tool, being more like a convenient wrapper generator than a
bolt-on high performance engine for CPython. Language implementations
like that of Lua have seen more progress on integrating solutions for
performance, it would seem.

As for a C-Python of the form requested, I suppose tools like Shed
Skin and RPython fit the bill somewhat, if a transparent solution is
needed where one writes in Python and it magically becomes fairly
efficient C or C++. Otherwise, Pyrex provides more explicit control
over what gets written in C and what remains in Python.

Paul

[hunter.grubbs]

On Dec 9, 3:23 pm, a...@pythoncraf t.com (Aahz) wrote:

In article <G62dnbBDl_Y0x8 HanZ2dnUVZ_gudn [e-mail] >,

Jack <nos...@invalid .comwrote:

I understand that the standard Python distribution is considered
the C-Python. Howerver, the current C-Python is really a combination
of C and Python implementation. There are about 2000 Python files
included in the Windows version of Python distribution. I'm not sure
how much of the C-Python is implemented in C but I think the more
modules implemented in C, the better performance and lower memory
footprint it will get.

Prove it. ;-)

Seriously, switching to more C code will cause development to bog down
because Python is so much easier to write than C.

I wonder if it's possible to have a Python that's completely (or at
least for the most part) implemented in C, just like PHP - I think
this is where PHP gets its performance advantage. Or maybe I'm wrong
because the core modules that matter are already in C and those Python
files are really a think wrapper. Anyhow, if would be ideal if Python
has performance similar to Java, with both being interpreted languages.

Could you provide some evidence that Python is slower than Java or PHP?
--
Aahz (a...@pythoncra ft.com) <* http://www.pythoncraft.com/

"Typing is cheap. Thinking is expensive." --Roy Smith

I'd like to provide some evidence that Python is *faster* than Java.
EVE online...emulat e that in JAVA please.

[Raymond Hettinger]

On Dec 9, 1:14 pm, "Jack" <nos...@invalid .comwrote:

I wonder if it's possible to have a Python that's completely (or at
least for the most part) implemented in C, just like PHP - I think
this is where PHP gets its performance advantage. Or maybe I'm wrong
because the core modules that matter are already in C and those Python
files are really a think wrapper. Anyhow, if would be ideal if Python
has performance similar to Java, with both being interpreted languages.

-1 This would seriously muck-up the evolution of the language.
Having a few building blocks written in C provides a basis
for writing very fast pure python (for example, sets, heapq,
itertools).
Beyond those building blocks, it is a step backwards to write in C.

Also, if you really need performance, the traditional solutions are to
use tools like Psyco or Pyrex.
Raymond

[hdante]

On Dec 9, 10:07 pm, "Jack" <nos...@invalid .comwrote:

I think most Java-Python benchmarks you can find online will indicate
that Java is a 3-10 times faster. A few here:
http://mail.python.org/pipermail/pyt...ry/125789.html
http://blog.snaplogic.org/?p=55

There are lies, damn lies and benchmarks. :)

Pure Python code is not going to beat Java code until the Python core
gets a JIT compiler. If you want fair results you have to either
disable the JIT in Java or use Psyco for Python. Otherwise you are
comparing the quality of one language implementation to the quality of a
JIT compiler.

The second articple does have a column for Psyco. It helps in some areas
but still not good enough to stand up against Java. Plus, Psyco is not the
main stream and has stopped development.

I'm also wondering, if Psyco is the right way to do, any reason it's not
being integrated into standard Python?

Instead of recurring to benchmarks, I recommend that you read the
following:

http://highscalability.com/youtube-architecture

There are no comparisons there, just a sample of what python and
psyco can achieve. For a language that isn't designed with speed in
mind, I think that's quite impressive.

[Bruno Desthuilliers]

Jack a écrit :

>>>I'm not sure
how much of the C-Python is implemented in C but I think the more
modules implemented in C, the better performance and lower memory
footprint it will get.

Prove it. ;-)

I guess this is subjective :)

If yes, benchmarks are not an argument. Else, you'll have hard time
making your point !-)

(hint: doing objective benchmarking is really a difficult art)

- that's what I felt in my experience
with web applications developed in Python and PHP. I wasn't able to
find a direct comparison online.

Could it be the case that you are comparing Python CGI scripts with
mod_php ? Anyway, since php is also usable (hem... maybe not the
appropriate qualificative) outside Apache, it should quite easy to make
a more serious test ?

Seriously: I never saw any benchmark where php was faster than Python
for any kind of stuff - unless of course you're trying to compare Zope
running as a CGI script with an hello world PHP script runned by mod_php.

[Bruno Desthuilliers]

hu***********@g mail.com a écrit :
(snip)

I'd like to provide some evidence that Python is *faster* than Java.

Then benchmark the time taken for the interpreter (oops, sorry: "VM") to
start !-)

[sturlamolden]

On 9 Des, 22:14, "Jack" <nos...@invalid .comwrote:

I understand that the standard Python distribution is considered
the C-Python. Howerver, the current C-Python is really a combination
of C and Python implementation. There are about 2000 Python files
included in the Windows version of Python distribution. I'm not sure
how much of the C-Python is implemented in C but I think the more
modules implemented in C, the better performance and lower memory
footprint it will get.

Donald Knuth, one of the fathers of modern computer science, is famous
for stating that "premature optimization is the root of all evil in
computer science." A typical computer program tends to have
bottlenecks that accounts for more than 90% of the elapsed run time.
Directing your optimizations anywhere else is futile.

Writing a program in C will not improve the speed of your hardware. If
the bottleneck is a harddisk or a network connection, using C will not
change that. Disk i/o is a typical example of that. It is not the
language that determines the speed by which Python or C can read from
a disk. It is the disk itself.

I had a data vizualization program that was slowed down by the need to
move hundreds of megabytes of vertex data to video RAM. It would
obviously not help to make the handful of OpenGL calls from C instead
of Python. The problem was the amount of data and the speed of the
hardware (ram or bus). The fact that I used Python instead of C
actually helped to make the problem easier to solve.

We have seen several examples that 'dynamic' and 'interpreted'
languages can be quite efficient: There is an implementation of Common
Lisp - CMUCL - that can compete with Fortran in efficiency for
numerical computing. There are also versions of Lisp than can compete
with the latest versions of JIT-compiled Java, e.g. SBCL and Allegro.
As it happens, SBCL and CMUCL is mostly implemented in Lisp. The issue
of speed for a language like Python has a lot to do with the quality
of the implementation. What really makes CMUCL shine is the compiler
that emits efficient native code on the fly. If it is possible to make
a very fast Lisp, it should be possible to make a very fast Python as
well. I remember people complaining 10 years ago that 'Lisp is so
slow'. A huge effort has been put into making Lisp efficient enough
for AI. I hope Python some day will gain a little from that effort as
well.

We have a Python library that allows us to perform a wide range of
numerical tasks at 'native speed': NumPy (http://www.scipy.org). How
such array libraries can be used to get excellent speedups is
explained here: http://home.online.no/~pjacklam/matl...mtt/index.html

We obviously need more effort to make Python more efficient for CPU
bound tasks. Particularly JIT compilation like Java, compilation like
Lisp or data specialization like Psyco.

But writing larger parts of the standard library in C is not a
solution.